2 citations · 2 across the 7 of their papers we have counts for
18 papers · 1 filter
Low-dimensional embeddings of high-dimensional data
Cyril de Bodt, Alex Diaz-Papkovich, Michael Bleher +18
Large collections of high-dimensional data have become nearly ubiquitous across many academic fields and application domains, ranging from biology to the humanities. Since working…
Directed Scattering for Knowledge Graph-based Cellular Signaling Analysis
Aarthi Venkat, Joyce Chew, Ferran Cardoso Rodriguez +3
Directed graphs are a natural model for many phenomena, in particular scientific knowledge graphs such as molecular interaction or chemical reaction networks that define cellular s…
DYMAG: Rethinking Message Passing Using Dynamical-systems-based Waveforms
Dhananjay Bhaskar, Xingzhi Sun, Yanlei Zhang +8
We present DYMAG, a graph neural network based on a novel form of message aggregation. Standard message-passing neural networks, which often aggregate local neighbors via mean-aggr…
A Flow Artist for High-Dimensional Cellular Data
Kincaid MacDonald, Dhananjay Bhaskar, Guy Thampakkul +5
We consider the problem of embedding point cloud data sampled from an underlying manifold with an associated flow or velocity. Such data arises in many contexts where static snapsh…
Inferring dynamic regulatory interaction graphs from time series data with perturbations
Dhananjay Bhaskar, Sumner Magruder, Edward De Brouwer +4
Complex systems are characterized by intricate interactions between entities that evolve dynamically over time. Accurate inference of these dynamic relationships is crucial for und…
Graph Fourier MMD for Signals on Graphs
Samuel Leone, Aarthi Venkat, Guillaume Huguet +3
While numerous methods have been proposed for computing distances between probability distributions in Euclidean space, relatively little attention has been given to computing such…